Unlock greater efficiency with workload personalization
FireOptimizer tailors inference to your exact needs, optimizing for speed, quality, and cost based on your unique data and usage patterns. Using techniques like adaptive speculative decoding, custom quantization, and dynamic workload handling, FireOptimizer learns and fine-tunes serving configurations from over 100,000 options—so your models run faster and more efficiently where it matters most.
Reinforcement Learning
Improve model quality with reinforcement learning
Make massive model behavior improvements simply by providing feedback. Define success criteria, give feedback, and improve outputs — no complex pipelines or ML expertise required. Make improvement automatics by defining evaluations to run autonomously.
Supervised Fine Tuning
Fine tune with your own data
Customize model behavior by fine-tuning with your own data. Fireworks makes supervised fine-tuning fast, reliable, and cost-effective with an optimized training stack. Train large, state-of-the-art models using advanced methods like quantization-aware training to achieve ideal results.
Deploy hundreds of fine-tuned models without added infra or costs. With Multi-LoRA, you can deploy a fine-tuned model for every customer and task—perfect for personalizing quality for B2B interactions. One-click deployment. Fully orchestrated.
